No Priors Ep. 95 | Best of 2024
Sarah Guo (host), Jensen Huang (guest), Andrej Karpathy (guest), Elad Gil (host), Sarah Guo (host), Andrej Karpathy (guest), Elad Gil (host), Guest (guest), Guest (guest), Elad Gil (host), Guest (guest), Guest (guest)
In this episode of No Priors, featuring Sarah Guo and Jensen Huang, No Priors Ep. 95 | Best of 2024 explores aI’s 2024 Frontiers: Data Centers, Exocortex, Agents, World Models, AGI This “best of 2024” episode of No Priors curates highlights from conversations with leading AI and tech figures, focusing on how AI is reshaping infrastructure, products, and human-computer interaction.
AI’s 2024 Frontiers: Data Centers, Exocortex, Agents, World Models, AGI
This “best of 2024” episode of No Priors curates highlights from conversations with leading AI and tech figures, focusing on how AI is reshaping infrastructure, products, and human-computer interaction.
Jensen Huang explains NVIDIA’s evolution into a vertically integrated data center platform, while Andrej Karpathy explores AI as an exocortex and why small, distilled models may power personal cognition.
Bret Taylor and Dylan Field discuss how AI agents and new UI paradigms will redefine digital business presence and interaction, from branded company agents to intelligent visual interfaces.
The Sora team, Dmitri Dolgov, and Alexandre Wang debate world modeling, autonomy, and the road to AGI, contrasting views on generalization, scaling, and the many small problems still to solve.
Key Takeaways
The new unit of computing is the data center, not the chip.
Jensen Huang argues that serious AI software requires designing and validating entire data centers, then disaggregating and selling components so NVIDIA’s stack can graft into all major cloud providers while keeping CUDA ubiquitous.
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Owning your exocortex may become as important as owning your data.
Andrej Karpathy suggests that if AI becomes an extension of our cognition, people will care deeply about owning model weights or having open-source fallbacks rather than entirely ‘renting their brain’ from closed platforms.
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Smaller, distilled models may provide a compact ‘cognitive core.’
Karpathy believes current LLMs waste capacity memorizing irrelevant details; with better data curation and distillation, performant models could shrink to around a billion parameters while using tools for external knowledge.
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Branded AI agents will become the primary digital presence for companies.
Bret Taylor predicts that by around 2025, interacting with a business will mean talking to its AI agent that can handle everything from support to commerce, eventually encompassing the full scope of what the company does.
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World-modeling from video may be a key ingredient in advanced intelligence.
The Sora team describes how training on video leads models to implicitly learn 3D structure, causality, and object interactions—potentially yielding better-than-human predictive capabilities as scale increases by simply ‘predicting data.’
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Going from impressive demos to driverless safety requires many more ‘nines.’
Dmitri Dolgov emphasizes that while modern models can quickly produce mind-blowing self-driving prototypes, removing the driver and achieving a safety record better than humans demands solving the long-tail of rare edge cases.
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The path to AGI may be incremental and domain-specific, not a sudden leap.
Alexandre Wang contends that AGI will resemble curing cancer more than inventing a vaccine: limited cross-domain generalization means many niche capabilities and data flywheels must be solved and built over decades, enabling society to adapt gradually.
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Notable Quotes
“The new unit of computing is the data center.”
— Jensen Huang
“If it’s not your weights, is it not your brain?”
— Andrej Karpathy
“Existing digitally will probably mean having a branded AI agent that your customers can interact with to do everything that they can do on your website.”
— Bret Taylor
“Building Sora as a world model is very similar to a big part of the intelligence that humans have.”
— Member of the OpenAI Sora team
“The path to AGI is going to look a lot more like curing cancer than developing a vaccine.”
— Alexandre Wang
Questions Answered in This Episode
If NVIDIA’s true product is a full data center, how might that reshape the balance of power between cloud providers, hardware vendors, and AI developers?
This “best of 2024” episode of No Priors curates highlights from conversations with leading AI and tech figures, focusing on how AI is reshaping infrastructure, products, and human-computer interaction.
Get the full analysis with uListen AI
As AI becomes an exocortex, what governance or standards might be needed to ensure meaningful ownership and portability of ‘your brain’ across platforms?
Jensen Huang explains NVIDIA’s evolution into a vertically integrated data center platform, while Andrej Karpathy explores AI as an exocortex and why small, distilled models may power personal cognition.
Get the full analysis with uListen AI
How should companies think about brand, trust, and liability when their primary customer touchpoint is an autonomous AI agent rather than a website or human staff?
Bret Taylor and Dylan Field discuss how AI agents and new UI paradigms will redefine digital business presence and interaction, from branded company agents to intelligent visual interfaces.
Get the full analysis with uListen AI
Will video-based world modeling like Sora’s eventually produce strong cross-modal generalization, or will Alexandre Wang’s view of limited transfer and niche flywheels prevail?
The Sora team, Dmitri Dolgov, and Alexandre Wang debate world modeling, autonomy, and the road to AGI, contrasting views on generalization, scaling, and the many small problems still to solve.
Get the full analysis with uListen AI
What evaluation frameworks and safety thresholds are necessary before society will widely accept systems like robotaxis and AGI-level models in everyday life?
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Transcript Preview
(instrumental music plays) Hi, No Priors listeners. I hope it's been an amazing 2024 for you all. Looking back on this year, we wanted to bring you highlights from some of our favorite conversations. First up, we have a clip with the one and only Jensen Huang, CEO of NVIDIA, the company powering the AI revolution. Since our 2023 No Priors chat with Jensen, NVIDIA's tripled in stock price, adding almost 100 billion of value each month of 2024, and entering the $3 trillion club. More recently, Jensen shared his perspective again with us, this time on why NVIDIA's no longer a chip company, but a data center ecosystem. Here's our conversation with Jensen. NVIDIA has moved into larger and larger, let's say, like unit of support for customers.
Mm-hmm.
So I think about it going from single chip to, you know-
Yeah.
... server to rack-
Yeah.
... NVL72. How do you think about that progression? Like what, what's next?
Uh-huh. That's great.
Like, could NVIDIA do a full data center?
Uh, in fact, we build full data centers. The way that we build everything, unless you're building... If you're developing software, you need the computer in its full manifestation. Um, we don't, we don't build PowerPoint slides and ship the chips and... We build a whole data center. And until we get the whole data center built up, how do you know the software works? Until you get the whole data center built up, how do you know your, you know, your fabric works and all the things that you expected the efficiencies to be? How do you know it's gonna really work at scale? And, and that's the reason why, that's the reason why it's not unusual to see somebody's actual performance be dramatically lower than their peak performance as shown in PowerPoint slides.
Mm-hmm.
And, and, and, and it's... Computing is just not used to... It's not what it used to be. You know, I say that the new unit of computing is the data center. That's, to us-
So that's what you have to deliver.
That's what we build. Now, we build a whole thing like that and then we... For every single thing that we... Every combination, uh, air cooled, x86, liquid cooled, grace, ethernet, InfiniBand, NVLink, no NVLink. You know what I'm saying? We build every single configuration. We have five super computers in our company today. Next year we're gonna build easily five more. So if you're serious about software, you build your own computers. If you're serious about software, then you're gonna build your whole computer, and we build it all at scale. This is the part that- Mm-hmm. ... that is really interesting. We build it at scale and we build it, uh, very vertically integrated. We optimize it, um, full stack, end-to-end, and then we disaggregate everything and we sell it in parts. That's the part that is completely, utterly remarkable about what we do. Mm-hmm. The complexity of, of that is just insane. And the reason for that is we wanna be able to graft our infrastructure into GCP, AWS, Azure, OCI. All of their control planes, security planes are all different, and all of the way they think about their cluster sizing, all different. And, um, uh, but yet we make it possible for them to all accommodate NVIDIA's architecture so that CUDA could be everywhere. That's really, really, in the end, the, the singular thought, you know, that we would like to have a computing platform that developers could use that's largely consistent, modulo, you know, 10% here and there because people's infrastructure are slightly optimized differently and... Modulo 10% here and there but, but everything they, they build will run everywhere. This is kind of the one of the principles of software that should never be g- given up. And it... And, and we, we, we protect it quite dearly. Uh, it makes it possible for our software engineers to build once, run everywhere. And, and that's because we recognize, uh, that the investment of software is the most expensive investment and it's easy to test. Uh, look at the size of the whole hardware industry and then look at the size of the world's industries. It's $100 trillion on top of this $1 trillion industry and that tells you something. The software that you build, you have to, you know, you basically maintain for as long as you shall live.
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